android

In my previous post, I explained how to integrate OpenCV on Android. In this post, let us integrate camera into our app to do some live testing in future. If you are visiting this blog for the first time, I recommend you to read OpenCV in Android – An Introduction (Part 1/2) before reading the current blog. By the end of this blog you will be having your basic app ready for testing any of your Computer Vision Algorithms on the images that you acquire from camera!

In order to use camera in our app, we need to give permissions for our app to access camera in the mobile. Open ‘app/src/main/AndroidManifest.xml’ and add the following lines of code.

Now add the following code into your OpenCVCamera.java file to see some action. After adding the following code try running the app on your device. I will explain the specifics in the later part of this blog.

If everything works fine, your screen should like the figure below. If your app shows a warning related to Camera Permissions, try going to settings and make sure that the camera permissions for the app is enabled. 🙂

But what is exaclty happening here? First you imported some necessary android and OpenCV classes for your app. To allow OpenCV to communicate with android camera functionalities, we implmented CvCameraViewListener2. The variable ‘CameraBridgeViewBase cameraBridgeViewBase’ acts as a bridge between camera and OpenCV. BaseLoaderCallback will give us information about whether OpenCV is loaded in our app or not. We also need some helper functions onResume, onCameraViewStarted, onCameraViewStopped and onCameraFrame to handle the events of the app.

With this you are ready with the basic set up of your development environment for Computer Vision application development in Android. I made some final edits to the app to make the camera view into Full Screen Activity and added some more event handlers. The code for the same can be accessed through the following github repo – LINK !

What’s next? In the next blog, I will discuss about how we can write our own custom C++ code for doing fun computer vision experiments using OpenCV on Android!

Hello world! I am very excited to write this particular blog on the setup of OpenCV in Android Studio. There are many solutions there online which include setting up OpenCV using Eclipse, Android NDK etc but I didn’t find a single reliable source for doing the same setup using Android Studio. So, we (Me and V.Avinash) finally came up with a feasible solution with which you can setup Native Development setup in Android environment for designing Computer Vision applications using OpenCV and C++!!!

A quick intro about me, I am a Computer Vision enthusiast with nearly 4 years of theoretical and practical experience in the field. That said, I am quite good at implementing CV algorithms on Matlab and Python. But with years, the same field has been developing rapidly from the mere academic interest to industrial interest. But most of the standard algorithms in this field are not really optimized to run in real-time (60 FPS) or not designed specifically for the mobile platform. This has caught my interest and I have been working on this since the Summer 2016. I think about various techniques and hacks for optimizing the existing algorithms for mobile platform and how to acquire (and play with) 3D data from the 2D camera during my free time from being a research assistant.

Before starting this project, I am assuming that you already have basic setup of Android Studio up and running on your machines and you have decent experience working on it.

If you don’t already have Android Studio, you can download and install it from the following link.

Once you have the Android Studio up and running, you can download OpenCV for Android from the following link. After downloading, extract the contents from the zip file and move it to a specific location. Let it be ‘/Users/user-name/OpenCV-android-sdk’. I am currently using Android Studio v2.2.3 and OpenCV v3.2

Now start the Android Studio and click on ‘Start a new Android Studio project’. This will open a new window. Specify your ‘Application Name’, ‘Company Domain’ and ‘Project Location’. Make sure you select the checkbox ‘Include C++ Support‘. Now click Next!

In the Activity customization window leave everything as it is without any edits and click Next.

In the Customize C++ Support, select C++ Standard: Toolchain Default and leave all the other checkboxes unchecked (for now, but you are free to experiment) and click Finish!

The Android Studio will take some time to load the project with necessary settings. Since you are developing an app that depends on Camera of your mobile, you can’t test these apps on an emulator. You need to connect your Android Phone (with developer options enabled) to computer and select the device when you pressed the debug option. After running the application, you should see the following on your mobile if everything works fine!

At this point of the project you have your basic native-development (C++ support) enabled in your app. Now let us start integrating OpenCV into your application.

Click on File -> New -> Import Module. In the pop-up window, give path to your ‘OpenCV-android-sdk/sdk/java’ directory and click on OK. You can find the module name as ‘openCVLibrary320’ and click Next, Finish to complete the importing.

Now, go to “openCVLibrary320/build.gradle” and change the following variables to those in the “app/build.gradle”: compileSdkVersion, buildToolsVersion, minSdkVersion, and targetSdkVersion. Sync the project after editing the gradle files. My “openCVLibrary320/build.gradle” file looks like this!

Add a new folder named ‘jniLibs’ to “app/src/main/” by right click -> New -> Directory. Copy and paste the directories in the ‘OpenCV-android-sdk/sdk/native/libs/’ to jniLibs folder in your app. After the import, remove all *.a files from your imported directories. At the end, you should have 7 directories with libopencv_java3.so files in them.

Now go to ‘app/CMakeLists.txt’ and link the OpenCV by doing the following (Refer to those lines following the [EDIT] block for quick changes):

# library. You should either keep the default value or only pass a
# value of 3.4.0 or lower.
cmake_minimum_required(VERSION 3.4.1)
# [EDIT] Set Path to OpenCV and include the directories
# pathToOpenCV is just an example to how to write in Mac.
# General format: /Users/user-name/OpenCV-android-sdk/sdk/native
set(pathToOpenCV /Users/sriraghu95/OpenCV-android-sdk/sdk/native)
include_directories(${pathToOpenCV}/jni/include)
# Creates and names a library, sets it as either STATIC
# or SHARED, and provides the relative paths to its source code.
# You can define multiple libraries, and CMake builds it for you.
# Gradle automatically packages shared libraries with your APK.
add_library( # Sets the name of the library.
native-lib
# Sets the library as a shared library.
SHARED
# Provides a relative path to your source file(s).
# Associated headers in the same location as their source
# file are automatically included.
src/main/cpp/native-lib.cpp )
# [EDIT] Similar to above lines, add the OpenCV library
add_library( lib_opencv SHARED IMPORTED )
set_target_properties(lib_opencv PROPERTIES IMPORTED_LOCATION /Users/sriraghu95/Documents/Projects/ComputerVision/OpenCVAndroid-AnIntroduction/app/src/main/jniLibs/${ANDROID_ABI}/libopencv_java3.so)
# Searches for a specified prebuilt library and stores the path as a
# variable. Because system libraries are included in the search path by
# default, you only need to specify the name of the public NDK library
# you want to add. CMake verifies that the library exists before
# completing its build.
find_library( # Sets the name of the path variable.
log-lib
# Specifies the name of the NDK library that
# you want CMake to locate.
log )
# Specifies libraries CMake should link to your target library. You
# can link multiple libraries, such as libraries you define in the
# build script, prebuilt third-party libraries, or system libraries.
target_link_libraries( # Specifies the target library.
native-lib
# Links the target library to the log library
# included in the NDK.
${log-lib} lib_opencv) #EDIT

Edit the ‘app/build.gradle’ set the cppFlags and refer to jniLibs source directories and some other minor changes, you can refer to the code below and replicate the same for your project. All new changes made on the pre-existing code are followed by comments “//EDIT”.

Once you are done with all the above steps, do sync the gradle and go to src/main/cpp/native-lib.cpp . To make sure that the project setup is done properly, start including OpenCV files in native-lib.cpp and it should not raise any errors.

Now make sure all your gradle files are in perfect sync and Rebuild the project once to check there are no errors in your setup.

By the end of this blog, we finished setting up OpenCV in your android project. This is a pre-requisite for any type of android application you want to build using OpenCV. Considering that there will be two types of possibilities using OpenCV in your application: a) Doing processing on images from your own personal library on mobiles and b) Doing real-time processing on live-feed from camera, I think this is best place to stop this part of the blog.

In my next post, I will be focusing on how to use camera in your application and do some simple processing on the data that you acquire from it.